Credit and Investment in Benin’s Economic Growth: Insights from ARDL Analysis
Bibliographic record
Abstract
This study examines the impact of credit and investment on Benin’s economic growth from 2000 to 2022, using the autoregressive distributed lag (ARDL) model. The analysis explores both short- and long-term relationships between Gross Capital Formation (GCF), Domestic Credit to the Private Sector (DOMCRED), trade openness (TRADE), exchange rates (EXRATE), Foreign Direct Investment (FDI), and inflation (INF). The findings reveal that 83.1% of GDP growth variance is explained by macroeconomic stability. Gross capital formation is a key driver of long-term growth, while inefficiencies in credit allocation limit the effectiveness of domestic credit. Exchange rate stability is vital for resilience, whereas trade openness shows adverse long-term effects, highlighting the need for diversification. The ARDL bounds test confirms a long-run equilibrium relationship among the variables. These results emphasize the need for policies aimed at improving credit allocation, stabilizing exchange rates, and promoting trade diversification to foster sustainable economic growth.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".